RESEARCH IN THE BIOCYBERNETICS LABORATORY these days is somewhat eclectic, but - as alway interdisciplinary. Our work typically involves integration of theory with real laboratory data, using biomodeling, computational and biosystems approaches. Our current problem domains are physiological systems, disease processes, pharmacology, and some post-genomic bioinformatics. The pedagogy of the lab involves development and exploitation of the synergistic and methodologic interface between structural and computational biomodeling with laboratory data, or computational systems biology, with a focus on integrated approaches for solving complex biosystem problems from sparse biodata (e.g. in physiology, medicine and pharmacology), as well as voluminous biodata (e.g. from genomic libraries and DNA array data).

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NEUROENDOCRINE PHYSIOLOGY RESEARCH

    Our primary neuroendocrine research project involves experimental studies of thyroid hormone regulation and metabolism.Our overall long-term goal is enhancement of understanding of the hierarchical mechanisms of control of thyroid hormone (TH) production, organ distribution metabolism and excretion in mammals and fishes.  Our approach is quantitative and integrative, with emphasis on both whole-organism and local organ TH regulation in health and disease states (integrated regulation of sources and sinks). Over the last 30 years, our contributions to the literature of TH metabolism and physiology have been realized using an integrated multidisciplinary investigative approach.  Physiology and biochemistry laboratory methodologies have been supplemented with two distinct and highly sophisticated biomodeling and experiment design approaches pioneered in our laboratory. Both treat in vivo derived multiorgan-whole-body data, one collected from steady state tracer kinetic experiments using multisite hormone constant infusion inputs, the other from multisite hormone pulse-dose transient response kinetic experiments. We are also currently embarking on a new modality, using a new technology, MicroPET, for whole-body dynamic functional imaging, for enhancing our in vivo TH kinetic analysis approach.

    We continue to emphasize three focus areas, in health versus disease states: (1) the arterio-enterohepatic system, particularly the role of intestinal components and processes in overall TH regulation (2) whole-body production of the hormone triiodothyronine (T3) from thyroxine (T4) in nonendocrine organs and from the thyroid; and (3) local organ T3 production rates, which have not been fully quantified in any organ, in any species, a problem we have nearly resolved in our most recent work.

    We are also exploring alternative mechanisms including a possible "chaos" explanation for the well-established pulsatile nature of secretion of hormones from the pituitary gland.  These studies utilize techniques of computational biology and nonlinear biomodeling, some developed by us, and others by collaborators at MIT, applied to human pituitary data supplied by collaborators at the University of Oregon.

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    These studies are focused on development of new kinetic modeling methodology for specific applications in life science research, particularly physiology, biochemistry and pharmacology. Emphasis is on dealing effectively with the particular limitations of biological data, and methods for designing kinetic experiments that optimize  use of resources, including both laboratory and experimental animal resources. Current projects include:

• Hierarchical neuroendocrine control of hormone metabolism and action,  at whole-organism,  neural, organ-system ,  cellular and molecular levels.
• Nonlinear mechanistic models of possibly chaotic behavior in neuroendocrine and cellular systems (e.g. is 'pulsatile' pituitary secretion 'chaotic'?).
• Model-based experiment-design techniques for optimizing experimental resources and strategies,  including Monte Carlo and dynamic system simulation testing of bioexperiment feasibility (e.g minimizing laboratory animal use).
• Estimating minimum and maximum values of kinetic parameters of interest that are otherwise unobtainable (unidentifiable).
• Hierarchical simulation models of the neuroendocrine control of hormone production, distribution metabolism and action, from organism to subcellular levels, with about a thousand coupled differential and algebraic equations, and cranking out emergent, complex nonlinear dynamical behavior.

    These activities complement our modeling methodology activities. They are the implementation of those efforts, and they provide some of the tools for performing our own experimental studies in neuroendocrinology.  W3DIMSUM and W3MCSIM are currently available and others are in advanced stages of development and soon will be available over the internet.

• W3DIMSUM: an expert system for determining the dimension of a sum of exponentials model, i.e. the optimum number of exponential terms, available now over the worldwide web. http://biocyb.cs.ucla.edu/dimsum/
• W3MCSIM: a program for Monte Carlo simulation of algebraic models of prospective and retrospective experimental data, available now over the worldwide web. www.biocyb.cs.ucla.edu/montecarlo/montecarlo.html
• PATIENTS: a multimedia patient education website (under construction).
• MAMCAT+: an interactive and expert system program for complete analysis of mammillary and catenary compartmental models
• OSS: a set of interactive programs for computing optimal blood sampling schedules for simple and complex kinetic studies
• CACA: a computer-aided chromatography analysis package
• GENES: an expert system for pharmacokinetic model discrimination
• RIELISA: an expert system program for radioimmunoassay (RIA) and ELISA assay analysis